In recent weeks, my YouTube videos have covered Probability concepts like Events, Sample Spaces, and Combinatorics. Today's video features exercises to test and cement your understanding of those concepts.
We will publish a new video from my "Probability for Machine Learning" course to YouTube every Wednesday. Playlist is here.
More detail about my broader "ML Foundations" curriculum (which also covers subject areas like Linear Algebra, Calculus, Statistics, Computer Science) and all of the associated open-source code is available in GitHub here.
Filtering by Category: Probability
Combinatorics
Combinatorics is a field of math devoted to counting. In this week's YouTube video, we use examples with real numbers to bring Combinatorics to life and relate it to Probability Theory.
We will publish a new video from my "Probability for Machine Learning" course to YouTube every Wednesday. Playlist is here.
More detail about my broader "ML Foundations" curriculum (which also covers subject areas like Linear Algebra, Calculus, Statistics, Computer Science) and all of the associated open-source code is available in GitHub here.
Multiple Independent Observations
In this week's YouTube tutorial, we consider probabilistic events where we have multiple independent observations — such as flipping a coin two or more times instead of just once.
We will publish a new video from my "Probability for Machine Learning" course to YouTube every Wednesday. Playlist is here.
More detail about my broader "ML Foundations" curriculum (which also covers subject areas like Linear Algebra, Calculus, Statistics, Computer Science) and all of the associated open-source code is available in GitHub here.
Events and Sample Spaces
In this week's YouTube tutorial, I introduce the most fundamental atoms of probability theory: events and sample spaces. Enjoy 😀
We will publish a new video from my "Probability for Machine Learning" course to YouTube every Wednesday. Playlist is here.
More detail about my broader "ML Foundations" curriculum (which also covers subject areas like Linear Algebra, Calculus, Statistics, Computer Science) and all of the associated open-source code is available in GitHub here.
What Probability Theory Is
This week, we start digging into the actual, uh, theory of Probability Theory. I also highlight the field's relevance to Machine Learning and Statistics. Enjoy 😀
We will publish a new video from my "Probability for Machine Learning" course to YouTube every Wednesday. Playlist is here.
More detail about my broader "ML Foundations" curriculum (which also covers subject areas like Linear Algebra, Calculus, Statistics, Computer Science) and all of the associated open-source code is available in GitHub here.
A Brief History of Probability Theory
This week's YouTube video is a quick introduction to the fascinating history of Probability Theory. Next week, we'll actually start digging into Probability Theory, uh, theory 😉
We will publish a new video from my "Probability for Machine Learning" course to YouTube every Wednesday. Playlist is here.
More detail about my broader "ML Foundations" curriculum (which also covers subject areas like Linear Algebra, Calculus, Statistics, Computer Science) and all of the associated open-source code is available in GitHub here.
Probability & Information Theory — Subject 5 of Machine Learning Foundations
Last Wednesday, we released the final video of my Calculus course, so today we begin my all-new YouTube course on Probability and Information Theory. This first video is an orientation to the course curriculum, enjoy!
We will publish a new video from my "Probability for Machine Learning" course to YouTube every Wednesday. Playlist is here.
More detail about my broader "ML Foundations" curriculum (which also covers subject areas like Linear Algebra, Calculus, Statistics, Computer Science) and all of the associated open-source code is available in GitHub here.